期刊
JOURNAL OF CLEANER PRODUCTION
卷 368, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2022.133122
关键词
Peer-to-Peer (P2P) energy trading; Renewable energy; Carbon-constrained energy planning; Fuzzy mixed-integer linear programming; Multi-period energy planning; Time-sliced based optimization model
资金
- Yayasan Sarawak Tun Taib Scholarship
- Ministry of Higher Education under Fundamental Research Grant Scheme [FRGS/1/2020/TK0/SWIN/03/3]
The global community is putting efforts in optimizing energy planning due to the deficiency of natural resources and serious climate change. Inter-entity energy planning, which allows internal trading of resources, has the potential to enhance energy planning by offering economic benefits and reducing environmental impacts. This study develops an inter-collaborative energy trading model to evaluate the effectiveness of collaboration and the economic benefits for involved peers. A case study in Malaysia is used to demonstrate the economic viability of inter-entity energy planning.
The deficiency of natural resources and serious climate change have driven the global community's efforts to optimize energy planning using various process integration approaches. The inter-entities energy planning that allows internal trading of resources presents a great potential to enhance energy planning. It is believed that the effective management of such relationships offers lower environmental impacts on top of the economic benefits. The developed inter-collaborative energy trading model gives a handy lens to evaluate the effectiveness of the suggested inter-entities collaboration and how it provides economic benefits for the involved peers. To demonstrate the economic viability of inter-entity energy planning, a multi-period Peer-to-peer (P2P) energy trading model - a horizontal cooperation among entities that allows internal energy trading, is developed in this work. An illustrative case study in Malaysia that involved three entities using the actual billing system adapted from Tenaga Nasional Berhad (TNB) is used to demonstrate the proposed methodology. First, two different single -objective optimization scenarios are considered: (i) minimization of electricity bills, and (ii) minimization of carbon emissions. A fuzzy optimization approach is then adopted in the case study to ensure the conflicting objectives are optimized simultaneously without over-prioritizing any of the objectives using the fuzzy sets theory. In the single-objective optimization scenarios, the entities managed to mitigate their total bills by USD 20,185.99/month and have a 82.55% carbon emissions reduction, respectively. Based on the results obtained from the multi-period P2P energy trading model using the fuzzy optimization approach, the involved entities can reduce their total electricity bill by USD 20,185.99/month (without over-prioritization of any of the entities involved) and achieve a total of 61% carbon emissions reduction. The optimal traded renewables unit cost of USD 0.089/kWh is determined via the sensitivity analysis conducted at the end of this work.
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